Atmospheric Modeling Division Publications: 2003

This page lists publication titles, citations and abstracts produced by NERL's Atmospheric Modeling Division for the year 2003, organized by Publication Type. Your search has returned
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One of the major technical challenges in calculating solar irradiance on the human form has been the complexity of the surface geometry (i.e. the surface normal vis a vis the incident radiation. Over 80 percent of skin cancers occur on the face, head, and back of the hands. The quantification, as well as the mapping of the anatomical distribution of solar radiation on the human form is essential if we are to study etiology of skin cancers or cataracts or immune system suppression. Utilizing advances in computer graphics, including high-resolution 3-dimensional mathematical representation of the human form, the calculation of irradiance has been attained in sub-centimeter precision. Lighting detail included partitioning of direct beam and diffuse sunlight, shadowing effects, and gradations of model surface illumination depending on model surface geometry and incident light angle. With the incorporation of ray tracing and radiosity algorithms, the results are not only realistic renderings, but also accurate representations of the distributions of light on the subject model. The calculation of light illumination various receptor points across the anatomy provides information about differential radiant exposure as a function of subject posture, orientation relative to the sun and sun elevation. The integration of a geodesic sun-tracking model into the lighting module enabled simulation of specific sun exposure scenarios, with instantaneous irradiance, as well as the cumulative radiant exposure, calculated for a given latitude, date, time of day, and duration. Illustration of instantaneous irradiance or cumulative radiant exposure is achieved using a false color rendering-mapping light intensity to color-creating irradiance or exposure isopleths. This approach may find application in the determination of the reduction in exposure that one achieves by wearing a hat, shirt, or sunglasses. More fundamentally, such as analysis could provide improved estimates of scenario-specific dose (i.e. absorbed radiant exposure) needed to develop dose-response function for sunlight-induced diseases. The United States Environmental Protection Agency through its Office of Research and Development partially funded and collaborated in the research described here under ct or assistance agreement number R829432010 to North Carolina State University. It has been subjected to Agency review and approved for publication.

The United States Environmental Protection Agency's National Exposure Research Laboratory is pursuing a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project is to develop improved methods for modeling the source through the air pathway to human exposure in significant microenvironments of exposure. Current particulate matter (PM) emission models, PART (used in the United States, except California) and EMFAC (used in California only), are suitable only for regional (county) scale modeling and emission inventories because of their dependence on aggregated vehicle-miles-traveled data. These emission models are not designed to estimate real-time emissions needed for human exposure studies near roadways. There is a need to develop site-specific real-time emission factor models for PM emissions. A microscale emission factor model for predicting site-specific real-time motor vehicle PM(MicroFacPM) emissions for TSP (total suspended particulate matter), PM (MicroFacPM) emissions for total suspended PM, PM less than 10 m aerodynamic diameter, and PM less than 2.5 m aerodynamic diameter has been developed. The algorithm used to calculate emission factors in MicroFacPM is disaggregated, and emission factors are calculated from a real-time fleet, rather than from a fleet-wide average estimated by a vehicle-miles-traveled weighting of the emission factors for different vehicle classes. MicroFacPM requires input information necessary to characterize the site-specific real-time fleet being modeled. Other variables required include average vehicle speed, time and day of the year, ambient temperature, and relative humidity.

EPA, through its Office of Research and Development, funded the research described here. This paper has been subjected to agency review and approved for publication.

JOURNAL

Relationship Between the Aerodynamic Roughness Length and the Roughness Density in Cases of Low Roughness Density

This paper presents measurements of roughness length performed in a wind tunnel for low roughness density. The experiments were performed with both compact and porous obstacles (clusters), in order to simulate the behavior of sparsely vegetated surfaces.

JOURNAL

Seasonal and Annual Modeling of Reduced Nitrogen Compounds Over the Eastern United States: Emissions, Ambient Levels, and Deposition Amounts

Detailed description of the distributions and seasonal trends of atmospheric nitrogen compounds is of considerable interest given their role in formation of acidic substances, tropospheric ozone and particulate matter and nutrient loading effects resulting from their deposition to sensitive ecosystems. While the oxidized nitrogen species have received considerable research and regulatory attention over the past several decades, little effort has been devoted towards quantifying the atmospheric budgets of reduced nitrogen compounds (NH2) associated with emissions of ammonia. The Regional Acid Deposition Model is enhanced to include detailed treatments of the physical and chemical processes regulating the fate of ammonia emissions and to model the interaction and chemical coupling of atmospheric NOx -SOx -NHx species. To account for uncertainties in magnitude and seasonal variation of ammonia emissions in the eastern United States are developed through successive model applications and comparison with measurements from regional networks of ambient concentrations and deposition amounts of various species. The resulting ammonia emissions show a distinct seasonal cycle with a maximum in summer followed by spring, fall, and winter. Correlations between model predicated ambient levels, gas/particle partitioning, and deposition amounts with measurements show good agreement on both an annual and seasonal basis with R2 in the 0.4-0.7 range for most species examined. Both model calculations and measurements indicate that during winter, large portions of the eastern U.S. are characterized by aerosols that are fully neutralized. Our model calculations for emission scenarios representative of the late 1980 - early 1990 period also indicate that reduced nitrogen species contribute 47(+/-8)% of the total nitrogen wet deposition in the eastern U.S.; this is in good agreement with 43(+/-9)% inferred from deposition measurements. These comparisons suggest that the model can capture the spatial and seasonal variability in distributions of various model species, the chemical coupling between reduced and oxidized nitrogen compounds in the troposphere, and the compositional characteristics of inorganic aerosol mass in the region. This document has been subjected to the U.S. EPA review and approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

JOURNAL

Seasonal Nh3 Emission Estimates for the Eastern United States Based on Ammonium Wet Concentrations and An Inverse Modeling Method

Significant uncertainty exists in the magnitude and variability of ammonia (NH3) emissions. NH3 emissions are needed as input for air quality modeling of aerosols and deposition of nitrogen compounds. Approximately 85% of NH3 emissions are estimated to come from agricultural non-point sources. We suspect a strong seasonal pattern in these NH3 emissions; however, current NH3 emission inventories lack intra-annual variability. If NH3 emissions are distributed evenly over a year, a default approach that has been used with air quality models, it can adversely affect model-predicted concentrations of nitrogen-containing compounds. In this paper, we apply a Kalman filter inverse modeling technique to deduce monthly 1990 NH3 emissions for the eastern United States. The United States Environmental Protection Agency (USEPA) Community Multiscale Air Quality (CMAQ) model and ammonium (NH4+) wet concentration data from the National Atmospheric Deposition Program (NADP) network are used. The results illustrate the strong seasonal differences in NH3 emissions that were anticipated, where NH3 emissions are considerably smaller during the colder seasons fall and winter and peak during summer. The results also suggest that the current USEPA 1990 National Emission Inventory (NEI) for NH3 may be too high. This is supported by a recent USEPA study of emission factors that proposes lower emission factors for cattle and swine, which are two of the largest sources of NH3 emissions in the inventory. This paper has been subjected to U.S. Environmental Protection Agency peer review and approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

Ambient air concentrations of particulate matter (atmospheric suspensions of solid of liquid materials, i.e., aerosols) continue to be a major concern for the U.S. Environmental Protection Agency (EPA). High particulate matter (PM) concentrations are associated not only with adverse human health effects, including increased morbidity and mortality arising from altered respiratory and cardiovascular function, but they also contribute to acid precipitation, regional climate change and visibility degradation.
This document has been reviewed and approved by the U.S. Environmental Protection Agency for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

The aerosol component of the Community Multiscale Air Quality (CMAQ) model is designed to be an efficient and economical depiction of aerosol dynamics in the atmosphere. The approach taken represents the particle size distribution as the superposition of three lognormal subdistributions, called modes. The processes of coagulation, particle growth by the addition of mass, new particle formation, are included. Time stepping is done with analytical solutions to the differential equations for the conservation of number, surface area, and species mass. The component considers both PM2.5 and PM10 and includes estimates of the primary emissions of elemental and organic carbon, dust and other species not further specified. Secondary species considered are sulfate, nitrate, ammonium, water and secondary organics from precursors of anthropogenic and biogenic origin. Extinction of visible light by aerosols is represented by two methods: a parametric approximation to Mie extinction and an empirical approach based upon field data. The algorithms that simulate cloud interactions with aerosols are also described. Results from box model and three-dimensional simulations are exhibited. This paper has been subjected to U.S. Environmental Protection Agency peer review and approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

JOURNAL

Diagnostic Evaluation of Numberical Air Quality Models With Specialized Ambient Observations: Testing the Community Multiscale Air Quality Modeling System (Cmaq) at Selected Sos 95 Ground Sites

Three probes for diagnosing photochemical dynamics are presented and applied to specialized ambient surface-level observations and to a numerical photochemical model to better understand rates of production and other process information in the atmosphere and in the model. However, care must be taken to ensure that rate and process information is not confounded by inappropriate averaging over these diurnally-changing photochemical dynamics. One probe, the [O3] response surface probe [O3]/[NOx], is used here as a chemical filter to select [NOx-limited hours in the observations and the simulations. Other probes used here are the fraction NOz/NOy, a measure of chemical aging, and a measure of the production efficiency of O3 per NOx converted, [O3] to [NOz]. The key ambient measurements for all three probes are accurate [NO2] and a reliable estimate of total NOy. Good agreement is shown between models and observations in cases where local photochemical production dominates and where model emissions inputs are thought to be mostly complete. We interpret this agreement to mean that the photochemical processing in CMAQ is substantially similar to that in the atmosphere. More importantly, we see that the three probes provide consistent information about photochemical, especially when used together. This paper has been reviewed in accordance with US EPA's peer review policies and approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

The multilayer biochemical dry deposition model (MLBC) described in the accompanying paper was tested against half-hourly eddy correlation data from six field sites under a wide range of climate conditions with various plant types. Modeled CO2, O3, SO2, and H2O (latent heat) fluxes were compared with measurements. Model outputs have good correlations with measurements at all locations. Correlation coefficients between model outputs and measurements at all sites range from 0.72 to 0.96 for CO2 flux, from 0.84 to 0.98 for H2O flux, from 0.77 to 0.95 for O3 flux, and from 0.36 to 0.86 for SO2 flux. Model sensitivity analyses were conducted to investigate the variation of model outputs due to measurement errors of input variables and to changes of environmental conditions such as changes in weather conditions. The MLBC outputs were also compared with outputs from the Multilayer Model (MLM) model [ Meyers et al., 1998 ] and the Regional Acid Deposition Model (RADM) [ Wesely, 1989 ] at two typical sites. Comparisons show that the MLBC performs better than the other two models. The model is suitable for use in nationwide dry deposition networks, for example, the Clean Air Status And Trends Network (CASTNet). It can be used to assist in describing total pollutant loadings to major ecosystems. With some modifications, the model may also be suitable for inclusion in region (meso-) scale numerical models, for example, the Community Multiscale Air Quality (CMAQ) model.

A multilayer biochemical dry deposition model has been developed based on the NOAA Multilayer Model (MLM) to study gaseous exchanges between the soil, plants, and the atmosphere. Most of the parameterizations and submodels have been updated or replaced. The numerical integration was improved, and an aerodynamic resistance based on Monin-Obukhov theory was added. An appropriate parameterization for the leaf boundary layer resistance was chosen. A biochemical stomatal resistance model was chosen based on comparisons of four different existing stomatal resistance schemes. It describes photosynthesis and respiration and their coupling with stomatal resistance for sunlit and shaded leaves separately. Various aspects of the photosynthetic process in both C3 and C4 plants are considered in the model. To drive the photosynthesis model, the canopy radiation scheme has been updated. Leaf area index measurements are adjusted to account for stem area index. A normalized soil water stress factor was applied to potential photosynthesis to account for plant response to both drought and water-logging stresses. A new cuticle resistance model was derived based on membrane passive transport theory and Fick's first law. It accounts for the effects of diffusivity and solubility of specific gases in the cuticle membrane, as well as the thickness of the cuticle membrane. The model is designed for use in the nationwide dry deposition networks, for example, the Clean Air Status And Trends Network (CASTNet), and mesoscale models, for example, the Community Multiscale Air Quality model (CMAQ) and even the Weather Research and Forecasting model (WRF).

Biogenic sources play an important role in ozone and particulate concentrations through emissions of volatile organic compounds. The same emissions also contribute to chronic toxic exposures from formaldehyde and acetaldehyde because each compound arises through primary and secondary processes. Anthropogenic sources may dominate over biogenic sources in both processes. Modeling tools are becoming able to compare how biogenic and anthropogenic sources contribute to both processes. Emissions models can predict formaldehyde and acetaldehyde emissions. Photochemical models can isolate how biogenic emissions contribute to the primary and secondary components of formaldehyde and acetaldehyde concentrations. Initial modeling results show that biogenic versus anthropogenic contributions depend on the pollutant and location. For the primary component, anthropogenic sources determine formaldehyde concentrations over most locations but acetaldehyde has large contribution from biogenic sources over rural locations. For the secondary component, both pollutants have a significant contribution from biogenic sources outside urban areas. This presentation discusses these contributions and their evaluation based a model system called Community Multiscale Air Quality model. This work has been funded wholly by the United States Environmental Protection Agency. It has been subjected to Agency review and approved for publication.

PRESENTATION

A Biogenic Role in Exposure to Two Toxic Compounds

12/10/2003

Hutzell, W T., G L. Gipson, G Pouliot, AND T. Pierce. A Biogenic Role in Exposure to Two Toxic Compounds. Presented at American Geophysical Union, San Francisco, CA, December 8-12, 2003.

Abstract:

Biogenic sources play an important role in ozone and particulate concentrations through emissions of volatile organic compounds. The same emissions also contribute to chronic toxic exposures from formaldehyde and acetaldehyde because each compound arises through primary and secondary processes. Anthropogenic sources may dominate over biogenic sources in both processes. Modeling tools are becoming able to compare how biogenic and anthropogenic sources contribute to both processes. Emissions models can predict formaldehyde and acetaldehyde emissions. Photochemical models can isolate how biogenic emissions contribute to the primary and secondary components of formaldehyde and acetaldehyde concentrations. Initial modeling results show that biogenic versus anthropogenic contributions depend on the pollutant and location. For the primary component, anthropogenic sources determine formaldehyde concentrations over most locations but acetaldehyde has large contribution from biogenic sources over rural locations. For the secondary component, both pollutants have a significant contribution from biogenic sources outside urban areas. This presentation discusses these contributions and their evaluation based on a model system called Community Multiscale Air Quality model. This work has been funded wholly by the United States Environmental Protection Agency. It has been subjected to Agency review and approved for publication.

Since the 1950's, the primary mission of the Atmospheric Modeling Division has been to develop and evaluate air quality simulation models. While the Division has traditionally focused the research on the meteorological aspects of these models, this focus has expanded in recent years to include emission processors, a critical but inaccurate component of air quality modeling. The need for emission modeling has been prompted by the realization that many emission processes require dynamically-responsive algorithms that account for the meteorological conditions and the need for innovative ways to evaluate emissions inventories. Three areas of concern are: 1) Biogenic emissions - development and integration of the third generation of the Biogenic Emissions Inventory System (BIES-3) 2). Fugitive Dust emissions - development and testing of geographical databases and a dynamic algorithm for making episodic estimates of wind blown fugitive dust and unpaved road dust. 3). Air-Quality Forecasting - creation of an emission processing system for an air quality forecasting system at the National Center for Environmental Prediction (NCEP). This paper has been reviewed in accordance with the U.S. Environmental Protection Agency's peer and administrative review policies. Mention of products or trade names does not constitute endorsement or recommendation of their use.

PRESENTATION

Application of the Urbanized Version of Mm5 for Houston

10/28/2003

Dupont, S., S. Burian, AND J.K S. Ching. Application of the Urbanized Version of Mm5 for Houston. Presented at 3 CMAS Workshop, Research Triangle Park, NC, October 27-29, 2003.

Abstract:

Since most of the primary atmospheric pollutants are emitted inside the roughness sub-layer (RSL) and consequently the first chemical reactions and dispersion occur in this layer, it is necessary to generate detailed meteorological fields inside the RSL to perform air quality modeling at high spatial resolutions. At neighborhood scale (on order of 1-km horizontal grid spacing), the meteorological fields are strongly influenced by the presence of the vegetation and building morphology of varying complexity, which requires developing more detailed treatment of the influence of canopy structures in the models and using additional morphological databases as input. The assumptions of the roughness approach, used by most of the mesoscale models, are unsatisfactory at this scale. Hence, a detailed urban and rural canopy parameterization (Dupont et al., 2003c), called DA-SM2-U, has been developed inside the Penn State/NCAR Mesoscale Model (MM5) to simulate the meteorological fields within and above the urban and rural canopies. DA-SM2-U uses the drag-force approach to represent the dynamic and turbulent effects of the buildings and vegetation, and a modified version of the soil model SM2-U (Dupont et al., 2003a and b), called SM2-U(3D), to represent the thermodynamic effects of the canopy elements. A first evaluation of DA-SM2-U on the city of Philadelphia (USA) (Dupont et al., 2003c) with a simple urban morphology representation has shown that the model is capable of simulating the important features observed in the urban and rural areas. The improvement of the urban canopy representation in mesoscale models requires the knowledge of more parameters. These parameters can be divided into three categories: i) the empirical parameters which are deduced from calibration of the models; ii) the "material parameters" which correspond to the physical properties of the surface materials of the canopy elements, they can be easily found in the literature from tables; and iii) the morphological parameters which depend on the structure and on the 3D arrangement of the canopy elements (buildings, vegetation, etc). The morphological parameters are variable from one city to another, and need to be averaged on few 100-m2 with a vertical resolution of a couple of meters to be used at neighborhood scales. Thus, these parameters may be the most difficult parameters to estimate.

Here, the DA-SM2-U version of MM5 is applied to Houston, Texas (USA), in order to study the influence of the morphological parameter resolution on the meteorological fields to know if a detailed resolution of these parameters is required or not for simulating at neighborhood scales. To provide the most accurate representation of these morphological parameters for the entire MM5 computational domain, a Houston GIS Urban Database has been created. This paper describes the DA-SM2-U model and the procedures used to create the morphological parameters on Houston, while the simulation results will be presented during the oral presentation.

This paper has been reviewed in accordance with United States Environmental Protection Agency's peer and administrative review policies and approved for presentation and publication

The talk will address the status of modeling of ammonia from a regional modeling perspective, yet the observations and comments should have general applicability. The air quality modeling system components that are central to modeling ammonia will be noted and a perspective on their contribution to the overall uncertainty will be given. Special attention to the overall importance of ammonia emissions and their uncertainty will be given with illustrations from inverse modeling. The capability of our physical and chemical modeling of the ammonia part of the inorganic system will be put in perspective vis a vis the overall inorganic system uncertainties. Issues related to estimating the dry deposition of ammonia will be noted. The large uncertainty in interpretations of the ammonia budget will then be raised, including our poor understanding of the regional or continental budget. Perspectives on local versus long-range transport from regional analyses will be given, modeled budget analyses will be presented and some discrepancies with conventional wisdom noted. This leads into a further discussion of issues that can affect attribution and introduce biases. The talk concludes with a set of recommendation of research directions that will help improve the modeling of ammonia, support better evaluation of models and aid interpretation of the ammonia system. Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official agency policy.

Consideration and movement for an urban air toxics control strategy is toward a community, exposure and risk-based modeling approach, with emphasis on assessments of areas that experience high air toxic concentration levels, the so-called "hot spots". This strategy will require information that accurately maps and characterizes the spatial and temporal variability of such pollutants. Many air toxic pollutants are active in photochemistry and ambient concentration levels will, therefore, depend on both the magnitude of the secondary products from the inflow regional background as well as from fresh emissions. In principle, the Community Multi-scale Air Quality (CMAQ) modeling system, using multi-scale modeling attributes can provide the ambient concentrations of air toxics from both regional and local sources and through advanced treatment of chemical, transport and deposition pathways. This paper explores the CMAQ capability to model air toxics at fine scale to meet the desired air toxics assessments objectives. This paper has been reviewed in accordance with United States Environmental Protection Agency's peer and administrative review policies and approved for presentation and publication.

PRESENTATION

Inverse Modeling to Estimate Nh3 Emission Seasonally and the Sensitivity to Uncertainty Representations

Inverse modeling has been used extensively on the global scale to produce top-down estimates of emissions for chemicals such as CO and CH4. Regional scale air quality studies could also benefit from inverse modeling as a tool to evaluate current emission inventories; however, underlying assumptions such as the linearity between emission and concentration changes can limit the applicability of inverse modeling. Ammonia (NH3) has been found to be a reasonable candidate because a strong linearity exists between NH3 emission adjustments and the response of modeled ammonium wet deposition. Further, the uncertainty in the emission estimates, especially on a monthly time scale, is quite large. While we anticipate that NH3 emissions from agricultural non-point sources have a strong seasonal pattern, the intra-annual variability of these primary NH3 sources is not yet understood well-enough to incorporate into current NH3 emission inventories. Along with the USEPA Community Multiscale Air Quality (CMAQ) model and NH4+ wet concentration data, an inverse modeling approach has been used to estimate monthly adjustments to the NH3 emission field over the Eastern United States. The first series of results, presented in Gilliland et al. [2003], offer the most comprehensive estimate of seasonal NH3 emission variability to date. These seasonal variations in NH3 emissions were shown to be essential for the prediction of nitrogen-containing compounds in that study. Further tests are now being conducted where a variety of uncertainty representations are considered in the inverse modeling calculations. These sensitivity tests will provide a more thorough range of emission adjustment estimates for each month and will test the rigor of the seasonal variability suggested by Gilliland et al. [2003].

This presentation will review how existing and future applications of satellite imagery can improve the accuracy of biogenic emission estimates. Existing applications of satellite imagery to biogenic emission estimates have focused on characterizing land cover. Vegetation data in the current version of the Biogenic Emissions Inventory System (BEIS) are largely based on the USGS National Land Cover Characteristics (NLCC) dataset, which is derived from AVHRR imagery. The NLCC data have been further augmented with a forest fraction database available at 1 km resolution from the U.S. Forest Service and based on analysis of AVHRR, LANDSAT, and ground-truth measurements. Xu et al. ("Estimates of biogenic emissions using satellite observation", Atmospheric Environment, vol. 36, 2002) demonstrate the utility of using monthly AVHRR data to more directly drive biogenic emission calculations. Beyond characterizing vegetation, satellite imagery is being used quite promisingly to perform inverse analysis of biogenic emissions. Researchers at Harvard University are using data from the GOME platform to derive formaldehyde patterns across the United States as a check against estimated isoprene emission distributions. The GOME data suggest that the distribution of isoprene is correctly represented in a model like BEIS and that the BEIS2 estimates may be underestimated. Satellite imagery can provide meteorological data fields that are vital to biogenic emission algorithms. For example, work supported by the TNRRCC has used GOES data to more accurately depict photosynthetically available radiation (PAR) for input to the GloBEIS program. In addition to current applications of satellite imagery, this presentation will review how emerging satellite imagery datasets may improve future modeling tools. Areas of possible improvements include refined temporal estimates in leaf biomass, quantitative measures of drought stress on vegetation, and better discrimination of vegetation species types.

The Arctic Council, having agreed to act to reduce exposures to a number of priority pollutants in the Arctic region, has initiated a mercury project via the Arctic Council Plan (ACAP). The project is being led by the Danish EPA with a Steering Group from all eight Arctic countries?Canada, Denmark, Finland, Iceland, Norway, Russia, Sweden, and United States. The overall project objective is to contribute to a decrease of mercury releases from Arctic countries. This will be accomplished partly by contributing to the development of a common regional framework for an action plan or strategy for the decrease of mercury emissions, and partly by evaluating and selecting one or a few specific point sources for implementation of control measures. It is felt that the decrease of mercury releases from key sources should serve as a demonstration of existing possibilities, giving inspiration to other control measures in the region.

A wind-tunnel study was conducted of dispersion from the site of the destroyed World Trade Center (WTC) in New York City. A scale model of lower Manhattan, including a scaled representation of the rubble pile, was constructed. The first phases of the study involved smoke visualization and measurements of flow patterns with winds from the west; the second phase involved the measurement of dispersion patterns resulting from tracer releases from the rubble pile. Neither the initial explosions nor the collapses of the towers have been simulated but, instead, dispersion from the smoldering rubble pile was modeled for the time period around two to six weeks after the catastrophe. Notable features included: strong horizontal recirculation patterns caused by a group of tall buildings not directly downwind acting as a single obstacle, vertical recirculation caused by a tall upwind building resulting in "pumping" of contaminants up the lee side to heights above the building top, and consistent alignment of flow directions with the street canyon axes at the lower levels, tending toward free-stream values at the upper elevations.

This research has been supported by the US Environmental Protection Agency. It has been subjected to agency review and approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use

PRESENTATION

Wind Tunnel Simulations to Assess Dispersion Around the World Trade Center Site

09/04/2003

Wind Tunnel Simulations to Assess Dispersion Around the World Trade Center Site. Presented at International Workshop on Physical Modeling of Flow & Dispersion Modeling, Prato, Italy, September 4, 2003.

Abstract:

There is no abstract available for this product. If further information is requested, please refer to the bibliographic citation and contact the person listed under Contact field.

PRESENTATION

Atmospheric Dispersion Modeling of Emissions from Ground Zero

06/24/2003

Huber, A H. Atmospheric Dispersion Modeling of Emissions from Ground Zero. Presented at First World Congress on Risk, Brussels, Belgium, June 22-25, 2003.

Abstract:

Since September 11, 2001 the EPA National Exposure Research Laboratory (NERL) has applied meteorological measurements and modeling to support WTC recovery assessments. The local meteorology is observed to be a key factor in both the diurnal and day-to-day changes in the observed ambient air concentration levels. Local wind patterns observed in lower Manhattan are somewhat modified by the local urban building environments. General patterns of plume transport and dispersion have been analyzed in comparison with mapped spatial distributions of measured particulate matter (PM) air concentrations. While emissions from the recovery site are unknown the temporal and spatial patterns of measurements are found to be strongly associated with the PM measurements and presently modeled pollution plume. A local scale CFD model simulation is being developed to better characterize emission sources and transport from ground zero to support the April 2003 assessment. The extent of travel of emissions and the effect of building influences, is broadening the understanding of exposure to residents and office workers near the WTC. This work has supported EPA's initial exposure and risk assessments to date. The development of refined modeling is ongoing with collaborators to support future EPA exposure and risk assessments. This work has been funded by the United States Environmental Protection Agency. It has been subjected to agency review and approved for publication.

PRESENTATION

Environmental Cfd Simulation and Visualization: Examples in Support of the Reconstruction of the Smoke/Dust Plume from the World Trade Center Site Following the Events of September 11, 2001

05/06/2003

Huber, A H., M. Freeman, AND K. H. Kuehlert. Environmental Cfd Simulation and Visualization: Examples in Support of the Reconstruction of the Smoke/Dust Plume from the World Trade Center Site Following the Events of September 11, 2001. Presented at Science Forum 2003, Washington, DC, May 5-7, 2003.

Abstract:

The Poster will present the process of Computational Fluid Dynamics (CFD) simulations through examples supporting the reconstruction of the smoke/dust plumes following the collapse of the WTC towers on September 11, 2001. Understanding the pathway of toxic air pollutants from source to human exposure in urban areas is of critical interest to the US Environmental Protection Agency, and finds immediate application in the Agency's role in Homeland Security. The collapse of the New York World Trade Center (WTC) Towers demonstrated clearly to EPA/ORD some of the shortcomings in conducting rapid exposure and risk analyses in urban areas, with their complex topology and large populations. Yet, rapid assessments of risk are vital to first responders, local officials, federal officials, and the public. The scientific shortcomings are especially serious for incidents that occur in an urban center where the understanding of airflow around large buildings is poor.

Computational Fluid Dynamic (CFD) simulations have long been used in the aerospace and automotive industries to evaluate air flow around planes and cars. CFD simulations are relatively new to applications in environmental science because of the temporal and spatial scales, and the complex chaotic nature of the physical processes in environmental problems. CFD techniques can be employed to describe the flow of pollutants (be they a plume from an event like the WTC collapse and fires, or be they the dispersion of some pollutant or agent) in the complex terrain that our urban areas represent. CFD simulations have the ability of closely matching the true geometry of the buildings and the "real world" physical processes. CFD simulations can be used directly or can be used as a foundation for developing reliable simplified models for rapid risk assessment.

ORD has adapted its research - using high performance computing technology and applications of Computational Fluid Dynamics (CFD) and Scientific Visualization to provide better descriptions of the complex air flow in urban environments and the distribution of pollutants carried by this air flow. The effort includes using actual field measurement data from New York, together with measurements from a scale-model of the WTC site in EPA's Fluid Modeling Facility, to provide evaluations of the CFD simulations of the WTC plume. The developments are a collaboration among EPA Office of Research and Development's National Exposure Research Laboratory and National Center for Exposure Assessment, EPA Office of Environmental Information's Scientific Visualization Center, and Fluent Inc. The applications are a collaboration with EPA Region 2 and the Environmental and Occupational Sciences Institute. The objective of this effort is to provide a sound scientific basis for rapid models of exposure and risk in urban areas for use by responders and emergency management personnel.

PRESENTATION

Forecasting Air Quality Over the United States.

05/05/2003

Schere, K L. Forecasting Air Quality Over the United States. Presented at Science Forum 2003, Washington, DC, May 5-7, 2003.

Abstract:

There is no abstract available for this product. If further information is requested, please refer to the bibliographic citation and contact the person listed under Contact field.

PRESENTATION

Forecasting Air Quality Over the United States

05/05/2003

Schere, K L. Forecasting Air Quality Over the United States. Presented at Science Forum 2003, Washington, DC, May 5-7, 2003.

Abstract:

Increased awareness of national air quality issues on the part of the media and the general public have recently led to more demand for short-term (1-2 day) air quality forecasts for use in assessing potential health impacts (e.g., on children, the elderly, and asthmatics) and potential mitigation actions in local communities (e.g., increased use of carpools and mass transit, decreased industrial operations). An emerging collaborative partnership between U.S. EPA and the National Oceanic and Atmospheric Administration (NOAA) will bring the strengths of these two Agencies' capabilities in atmospheric measurements and modeling in developing an operational capability for producing national modeling guidance for short-term air quality forecasts for ozone and particulate matter. EPA will contribute through its national assimilation, analysis, and dissemination of ambient air quality data and emissions data, as well as its air quality modeling capability. NOAA brings expertise in operational meteorological modeling and product development and dissemination. Local air quality forecasts will be made by state and local air quality management agencies, based in part upon the national guidance provided by the EPA/NOAA partnership. The initial operational capability will provide 1-2 day ozone forecast guidance for the Northeast U.S. on a daily basis by September 2004. Model development and testing of the operational system will be conducted from now through the summer 2004 ozone season.The initial operational modeling system, to be run at NOAA's National Center for Environmental Prediction (NCEP), will consist of NOAA's Eta meteorological model, linked with EPA's Community Multiscale Air Quality (CMAQ) model. The coupled system will produce hourly forecasts of ozone and other photooxidants on a three-dimensional model grid of application covering the eastern U.S. with a grid resolution of 12 km. Hourly meteorological data will be provided by the Eta model to the CMAQ model. In addition, source emissions data from EPA's national inventory and ozone air quality data from EPA's AIRNow database will be provided to the modeling system on an hourly basis. Model guidance will be availalble to local forecasters by early afternoon to make the air quality forecast for the following day. Over the next five years the model domain will be extended to cover the entire continental U.S. and model capability will be extended to provide forecast guidance on fine particulate matter.

Since the inception of the Clean Air Act (CAA) in 1969, atmospheric models have been used to assess source-receptor relationships for sulfur dioxide and total suspended particulate matter (TSP) in the urban areas. The focus through the 1970's has been on the Gaussian dispersion models for non-reactive pollutants. The 1977 Amendments to the CAA mandated the use of dispersion models for assessing compliance with the relevant National Ambient Air Quality Standards (NAAQS) when new sources of pollution are permitted and for prevention of significant deterioration. In the 1980's, the focus has been on the secondary pollutants (e.g., ozone, acid rain), which led to the development of grid-based photochemical models to better understand the urban and regional scale pollution. In the 1990's, attention was paid to the development of one-atmosphere models to deal with multiple pollutants. The new NAAQS for ozone and fine particulate matter (PM 2.5) that were promulated in the 1997 call for the use of one-atmosphere models in designing multi-pollutant emission control strategies. In the 2000's, there is a considerable interest in the development of integrated airshed-watershed models to properly assess the effects of atmospheric pollution on sensitive ecosystems. Air quality models can help improve our understanding of the transport and fate of pollutants, and are essential tools for designing meaningful and effective emission control strategies. Future applications of air quality models will be towards the prediction and improved understanding of human exposure, especially in urban areas, and intercontinental-cross oceanic hemispheric air pollutant transport.